Publication: System dynamic modeling: An alternative method for budgeting
Issued Date
2008-01-01
Resource Type
ISSN
15244733
10983015
10983015
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2-s2.0-41749124342
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Mahidol University
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SCOPUS
Bibliographic Citation
Value in Health. Vol.11, No.SUPPL. 1 (2008)
Suggested Citation
Witsanuchai Srijariya, Arthorn Riewpaiboon, Usa Chaikledkaew System dynamic modeling: An alternative method for budgeting. Value in Health. Vol.11, No.SUPPL. 1 (2008). doi:10.1111/j.1524-4733.2008.00375.x Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/19796
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Title
System dynamic modeling: An alternative method for budgeting
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Abstract
Objectives: To construct, validate, and simulate a system dynamic financial model and compare it against the conventional method. Methods: The study was a cross-sectional analysis of secondary data retrieved from the National Health Security Office (NHSO) in the fiscal year 2004. The sample consisted of all emergency patients who received emergency services outside their registered hospital-catchments area. The dependent variable used was the amount of reimbursed money. Two types of model were constructed, namely, the system dynamic model using the STELLA software and the multiple linear regression model. The outputs of both methods were compared. Results: The study covered 284,716 patients from various levels of providers. The system dynamic model had the capability of producing various types of outputs, for example, financial and graphical analyses. For the regression analysis, statistically significant predictors were composed of service types (outpatient or inpatient), operating procedures, length of stay, illness types (accident or not), hospital characteristics, age, and hospital location (adjusted R2= 0.74). The total budget arrived at from using the system dynamic model and regression model was US$12,159,614.38 and US$7,301,217.18, respectively, whereas the actual NHSO reimbursement cost was US$12,840,805.69. Conclusions: The study illustrated that the system dynamic model is a useful financial management tool, although it is not easy to construct. The model is not only more accurate in prediction but is also more capable of analyzing large and complex real-world situations than the conventional method. © 2008, International Society for Pharmacoeconomics and Outcomes Research (ISPOR).